论文标题
使用Imagenet模型和468个面部地标的时间图像进行深泡沫检测
Deepfake Detection using ImageNet models and Temporal Images of 468 Facial Landmarks
论文作者
论文摘要
本文介绍了我们的结果和有关使用时间图像进行深层检测的结果。我们通过使用这些面部地标上的像素值构造图像（称为时间图像），建立了在给定视频的468个面部标记横跨给定视频框架中的临时关系。 CNN能够识别给定图像的像素之间存在的空间关系。研究了10种不同的成像网模型。
This paper presents our results and findings on the use of temporal images for deepfake detection. We modelled temporal relations that exist in the movement of 468 facial landmarks across frames of a given video as spatial relations by constructing an image (referred to as temporal image) using the pixel values at these facial landmarks. CNNs are capable of recognizing spatial relationships that exist between the pixels of a given image. 10 different ImageNet models were considered for the study.
